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ee72bd1b09
Add a parser_perf test. Skip the extra filter stage and change the regex to match on category=TRACE lines only. Also flip the check in analysis_runner, since we only have a few tracer classes in the beginning, the rest are tracer entries. |
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tracer | ||
gsttr-stats.py | ||
Makefile | ||
README |
# Add a python api for tracer analyzers The python framework will parse the tracer log and aggregate information. the tool writer will subclass from the Analyzer class and override methods: 'handle_tracer_class(self, entry)' 'handle_tracer_entry(self, entry)' Each of those is optional. The entry field is the parsed log line. In most cases the tools will parse the structure contained in event[Parser.F_MESSAGE]. A tool will use an AnalysisRunner to chain one or more analyzers and iterate the log. A tool can also replay the log multiple times. If it does, it won't work in 'streaming' mode though (streaming mode can offer live stats). ## TODO ### gst shadow types Do we want to provide classes like GstBin, GstElement, GstPad, ... to aggregate info. One way to get them would be to have a GstLogAnalyzer that knows about data from the log tracer and populates the classes. Tools then can do e.g. pad.name() # pad name pad.parent().name() # element name pad.peer().parent() # peer element pad.parent().state() # element state ### improve class handling We already parse the tracer classes. Add helpers that for numeric values that extract them, and aggregate min/max/avg. Consider other statistical information (std. deviation) and provide a rolling average for live view. ## Examples ### Sequence chart generator (mscgen) 1.) Write file header 2.) collect element order Replay the log and use pad_link_pre to collect pad->peer_pad relationship. Build a sequence of element names and write to msc file. 3.) collect event processing Replay the log and use pad_push_event_pre to output message lines to mscfile. 4.) write footer and run the tool. ## Latency stats 1.) collect per sink-latencies and for each sink per source latencies Calculate min, max, avg. Consider streaming interface, where we update the stats e.g. once a sec 2.) in non-streaming mode write final statistic ## cpu load stats Like latency stats, for cpu load. Process cpu load + per thread cpu load. ## top Combine various stats tools into one. # Improve tracers ## log * the log tracer logs args and results into misc categories * issues * not easy/reliable to detect its output among other trace output * not easy to match pre/post lines * uses own do_log method, instead of gst_tracer_record_log * if we also log structures, we need to log the 'function' as the structure-name, also fields would be key=(type)val, instead of key=value * if we switch to gst_tracer_record_log, we'd need to register 27 formats :/